Abstract
Molecularly imprinted polymers (MIPs) are widely used as robust biomimetic recognition layers in sensing devices targeting a wide variety of analytes including microorganisms such as bacteria. Assessment of imprinting success and selectivity toward the target is of great importance in MIP quality control. We generated Escherichia coli-imprinted poly(styrene-co-DVB) as a model system for bacteria-imprinted polymers via surface imprinting using a glass stamp with covalently immobilized E. coli. Confocal Raman Microscopy was successfully employed to visualize bacteria, imprints, and polymer and to distinguish them from each other. The method has proven highly feasible for assessing if imprinting had been successful. In addition, we developed a method for selectivity investigation of bacteria MIPs based on combining Confocal Raman Microscopy and Partial Least Squares Discriminant Analysis (PLS-DA). The Raman spectra of E. coli and Bacillus cereus were acquired on E. coli-imprinted poly(styrene-co-DVB) and used to establish a PLS-DA model for differentiating between the bacteria species. Model validation demonstrated a correct classification of 95% of Raman spectra, indicating sufficient accuracy of the model for future use in MIP selectivity studies. Simultaneous differentiation of 3 bacteria species (E. coli, B. cereus, and Lactococcus lactis) on E. coli-imprinted poly(styrene-co-DVB) proved more difficult, which might be due to the limited depth resolution of the confocal Raman microscope resulting in the presence of interfering signals from the polymer substrate. It might be possible to overcome this obstacle by selective enhancement of the Raman signals originating from bacteria surfaces, such as tip enhanced Raman spectroscopy.
Highlights
It is important to detect and identify pathogenic bacteria in clinical environments, where multidrug-resistant bacteria are becoming a serious threat to public health,[1] and in food and water safety
E. coli-sensitive sensing devices have been developed based on E. coli-selective molecularly imprinted polymers (MIPs) as artificial receptors combined with transducers such as quartz crystal microbalances (QCMs) for direct detection of the microorganism in aqueous solution.[7]
We have presented the successful development of a novel method for the assessment of MIP selectivity based on Confocal Raman Microscopy and Partial Least Squares Discriminant Analysis (PLS-DA)
Summary
It is important to detect and identify pathogenic bacteria in clinical environments, where multidrug-resistant bacteria are becoming a serious threat to public health,[1] and in food and water safety. To assess the feasibility of the Raman Microscopy-PLS-DA approach to identify bacteria (namely, B. cereus and Lactococcus lactis) from a mixture on E. coli-imprinted poly(styrene-co-DVB), model calibration relied on one calibration spot per bacterium (20 spectra per species). Applying Raman Microscopy-PLS-DA to assess the selectivity of E. coli-imprinted polymers requires the possibility to correctly identify different bacteria species from a mixture. This is especially the case when one desires to investigate selectivity of the MIP at conditions where several strains are competing for rebinding at once. Difficulties in bacteria distinction beyond 2 different species on MIPs can be attributed to the fact that class differentiation relies on very small spectral differences, because most of the Raman signal intensity observed originates from E. coli-imprinted poly(styrene-co-DVB). Tip-enhanced Raman scattering could serve to enhance bacteria signals exclusively without increasing the intensity of the polymer background spectrum, which may help in solving this problem
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
